Pub Date : 2023-04-01DOI: 10.1784/insi.2023.65.4.217
Yunzhong Xia, Wanxiang Li, Yangyang Gao
Due to the complex and variable operating conditions of motor bearings, it is difficult for a deep autoencoder (DAE) to effectively extract valuable fault features from the raw vibration signal, which makes it difficult to identify faults. To enhance the extraction ability of the deep features of a network model and improve the accuracy of fault identification, this paper proposes a fault diagnosis method for motor bearings based on a deep sparse binary autoencoder and principal component analysis (PCA). Firstly, a deep sparse binary autoencoder is constructed by combining an autoencoder with a binary processor to improve the ability to extract deep features. Secondly, principal component analysis is used to fuse high-dimensional features to reduce dimensionality and eliminate redundant information existing in the deep features. Finally, fused deep features are input into a Softmax classifier to train the intelligent fault diagnosis model. The proposed method is validated on a rolling bearing dataset. Compared with existing methods, the experimental results show that this method can effectively extract robust features from the original vibration signals and improve the fault diagnosis results.
{"title":"A novel motor bearing fault diagnosis method based on a deep sparse binary autoencoder and principal component analysis","authors":"Yunzhong Xia, Wanxiang Li, Yangyang Gao","doi":"10.1784/insi.2023.65.4.217","DOIUrl":"https://doi.org/10.1784/insi.2023.65.4.217","url":null,"abstract":"Due to the complex and variable operating conditions of motor bearings, it is difficult for a deep autoencoder (DAE) to effectively extract valuable fault features from the raw vibration signal, which makes it difficult to identify faults. To enhance the extraction ability of the deep\u0000 features of a network model and improve the accuracy of fault identification, this paper proposes a fault diagnosis method for motor bearings based on a deep sparse binary autoencoder and principal component analysis (PCA). Firstly, a deep sparse binary autoencoder is constructed by combining\u0000 an autoencoder with a binary processor to improve the ability to extract deep features. Secondly, principal component analysis is used to fuse high-dimensional features to reduce dimensionality and eliminate redundant information existing in the deep features. Finally, fused deep features\u0000 are input into a Softmax classifier to train the intelligent fault diagnosis model. The proposed method is validated on a rolling bearing dataset. Compared with existing methods, the experimental results show that this method can effectively extract robust features from the original vibration\u0000 signals and improve the fault diagnosis results.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128387898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1784/insi.2023.65.4.209
Yuanling Chen, Yaguang Jin, Qiang Wan, Yuan Liu
By exploring the mapping relationship between the multi-directional data and fault characteristics of bearings, a time-frequency analysis method for considering the multi-directional acoustic emission (AE) data of bearings is proposed. Firstly, using the full vector spectrum (FVS) theory, the full vector sound spectrogram of the dual-channel AE signal of a bearing is extracted to enhance the representation of the fault state using time-frequency characteristics. Then, the obtained full vector sound spectrogram is transformed into a specific size as the input feature map and a convolutional neural network (CNN) classifier model is established. Next, the Softmax classifier is used to classify the bearing faults in order to realise the intelligent fault diagnosis of an ultra-low-speed rolling bearing. The comparison of the different models shows that the average recognition accuracy using the full vector sound spectrogram CNN model can reach 95.61%, which is better than the other three methods. The feature extraction using the full vector sound spectrogram feature analysis method has a high degree of recognition for bearing faults in an ultra-low-speed state and can provide high accuracy and stability under noisy conditions.
{"title":"Study on fault diagnosis of ultra-low-speed rolling bearings based on full vector sound spectrogram","authors":"Yuanling Chen, Yaguang Jin, Qiang Wan, Yuan Liu","doi":"10.1784/insi.2023.65.4.209","DOIUrl":"https://doi.org/10.1784/insi.2023.65.4.209","url":null,"abstract":"By exploring the mapping relationship between the multi-directional data and fault characteristics of bearings, a time-frequency analysis method for considering the multi-directional acoustic emission (AE) data of bearings is proposed. Firstly, using the full vector spectrum (FVS) theory,\u0000 the full vector sound spectrogram of the dual-channel AE signal of a bearing is extracted to enhance the representation of the fault state using time-frequency characteristics. Then, the obtained full vector sound spectrogram is transformed into a specific size as the input feature map and\u0000 a convolutional neural network (CNN) classifier model is established. Next, the Softmax classifier is used to classify the bearing faults in order to realise the intelligent fault diagnosis of an ultra-low-speed rolling bearing. The comparison of the different models shows that the average\u0000 recognition accuracy using the full vector sound spectrogram CNN model can reach 95.61%, which is better than the other three methods. The feature extraction using the full vector sound spectrogram feature analysis method has a high degree of recognition for bearing faults in an ultra-low-speed\u0000 state and can provide high accuracy and stability under noisy conditions.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122753558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1784/insi.2023.65.4.188
V. Kamenov, B. Velev
The following acoustic characteristics are measured in this study: the velocity of longitudinal waves Cl and the attenuation coefficient of ultrasound δ in samples of grey cast iron, which are obtained by centrifugal casting. The correlations between the mechanical properties, the acoustic non-destructive testing characteristics and the structure formation of the test specimens of cast iron with flaked graphite are studied. The study shows that data on the structure formation can be obtained, followed by the mechanical properties, hardness and tensile strength, by measuring the speed and attenuation of the ultrasound.
{"title":"Research into the relationship of mechanical properties of grey cast iron through acoustic non-destructive testing","authors":"V. Kamenov, B. Velev","doi":"10.1784/insi.2023.65.4.188","DOIUrl":"https://doi.org/10.1784/insi.2023.65.4.188","url":null,"abstract":"The following acoustic characteristics are measured in this study: the velocity of longitudinal waves Cl and the attenuation coefficient of ultrasound δ in samples of grey cast iron, which are obtained by centrifugal casting. The correlations between the mechanical\u0000 properties, the acoustic non-destructive testing characteristics and the structure formation of the test specimens of cast iron with flaked graphite are studied. The study shows that data on the structure formation can be obtained, followed by the mechanical properties, hardness and tensile\u0000 strength, by measuring the speed and attenuation of the ultrasound.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"397 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126745619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-01DOI: 10.1784/insi.2023.65.4.193
Hongjie Zhang, Hao Xuan, Rongxin Gao
A new type of magnetising and magnetic flux leakage (MFL) inspection system is designed, in which an ARM microprocessor-based measuring circuit and a novel magnetising device developed by the authors are combined to detect the magnetic field around a pit defect in a steel sheet. Based on a series of careful detection experiments, the spatial distributions of the three-dimensional (3D) MFL components of some typical artificial defects are described and observation, comparison, feature extraction and analyses are then carried out. The results show that the 3D components of the MFL field produced by the newly proposed magnetising device present some distinctive properties compared to those made by the traditional magnetising device. They involve rich information that exhibits close correlations to the morphology and critical parameters of the pit defects on the near side of the steel sheet, demonstrating the feasibility, effectiveness and reliability of the newly proposed inspection system, as well as laying a good foundation for the testing, evaluation or reconstruction and inversion of the pit defect.
{"title":"A new type of magnetising and magnetic flux leakage inspection system for the non-destructive testing of pit defects on the surface of a steel sheet","authors":"Hongjie Zhang, Hao Xuan, Rongxin Gao","doi":"10.1784/insi.2023.65.4.193","DOIUrl":"https://doi.org/10.1784/insi.2023.65.4.193","url":null,"abstract":"A new type of magnetising and magnetic flux leakage (MFL) inspection system is designed, in which an ARM microprocessor-based measuring circuit and a novel magnetising device developed by the authors are combined to detect the magnetic field around a pit defect in a steel sheet. Based\u0000 on a series of careful detection experiments, the spatial distributions of the three-dimensional (3D) MFL components of some typical artificial defects are described and observation, comparison, feature extraction and analyses are then carried out. The results show that the 3D components of\u0000 the MFL field produced by the newly proposed magnetising device present some distinctive properties compared to those made by the traditional magnetising device. They involve rich information that exhibits close correlations to the morphology and critical parameters of the pit defects on the\u0000 near side of the steel sheet, demonstrating the feasibility, effectiveness and reliability of the newly proposed inspection system, as well as laying a good foundation for the testing, evaluation or reconstruction and inversion of the pit defect.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126536948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1784/insi.2023.65.3.161
B. Hamza, K. Refassi
Order analysis is a powerful technique for analysing the vibration signals of rotating machinery under a known variable rotational speed. It requires the installation of speed-measuring devices; however, these devices cannot be installed in most machines due to design or cost reasons. In this study, a new method based on a time delay and resampling technique is introduced to estimate the instantaneous frequency (IF) of the vibration signal of a gear system. Order analysis techniques are used to extract the gear fault features. The performance of the proposed method is validated using simulated data from a gear system under speed-up and speed-down conditions.
{"title":"Novel tacholess order tracking method for gear fault diagnosis under speed-up and speed-down conditions","authors":"B. Hamza, K. Refassi","doi":"10.1784/insi.2023.65.3.161","DOIUrl":"https://doi.org/10.1784/insi.2023.65.3.161","url":null,"abstract":"Order analysis is a powerful technique for analysing the vibration signals of rotating machinery under a known variable rotational speed. It requires the installation of speed-measuring devices; however, these devices cannot be installed in most machines due to design or cost reasons.\u0000 In this study, a new method based on a time delay and resampling technique is introduced to estimate the instantaneous frequency (IF) of the vibration signal of a gear system. Order analysis techniques are used to extract the gear fault features. The performance of the proposed method is validated\u0000 using simulated data from a gear system under speed-up and speed-down conditions.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"185 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120866145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1784/insi.2023.65.3.139
Gang Wang, Yuting Li, Qiong Xiao, Wenhui Li
Remote field eddy current (RFEC) methods are widely applied for detecting pipeline defects. However, current RFEC methods cannot distinguish inner diameter (ID) defects from outer diameter (OD) defects. In addition, existing RFEC probes are usually driven by an extremely low-frequency signal, which reduces the detection efficiency. To address these issues, a novel external RFEC probe is designed to improve the detection performance. First, the probe structure is designed using a simulation tool. Second, the excitation and structural parameters are optimally selected. Finally, the relationships between the signal features and the defect dimensions are analysed. The results show that the probe can realise the RFEC effect without shield cages, the exciting frequency is significantly improved and the phase angle can be used to classify ID and OD defects.
{"title":"Finite element study of remote field eddy current methods for inner diameter and outer diameter pipeline defect classification","authors":"Gang Wang, Yuting Li, Qiong Xiao, Wenhui Li","doi":"10.1784/insi.2023.65.3.139","DOIUrl":"https://doi.org/10.1784/insi.2023.65.3.139","url":null,"abstract":"Remote field eddy current (RFEC) methods are widely applied for detecting pipeline defects. However, current RFEC methods cannot distinguish inner diameter (ID) defects from outer diameter (OD) defects. In addition, existing RFEC probes are usually driven by an extremely low-frequency\u0000 signal, which reduces the detection efficiency. To address these issues, a novel external RFEC probe is designed to improve the detection performance. First, the probe structure is designed using a simulation tool. Second, the excitation and structural parameters are optimally selected. Finally,\u0000 the relationships between the signal features and the defect dimensions are analysed. The results show that the probe can realise the RFEC effect without shield cages, the exciting frequency is significantly improved and the phase angle can be used to classify ID and OD defects.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125098350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Coated steel belts (CSBs) are the primary load-bearing components of elevators. As a result, they may experience severe fatigue failure during their long-term service. In this study, a flexible fatigue fixture for CSBs is designed to simulate the CSB fatigue damage process for implementing a tensile fatigue test. The magnetic induction intensity signal on the surface of the CSB in a geomagnetic field environment is recorded using a high-precision weak magnetic sensor. Moreover, the CSB fatigue damage process is monitored online via the acquired magnetic induction intensity value. The fatigue test results indicate the following: the variation in the magnetic induction intensity signal curve can reflect the entire fatigue failure process when the CSB is under stress; the fatigue failure process of the steel wire inside the CSB does not occur smoothly as its progress occurs in stages; and the variation trend in the residual value between the magnetic induction intensity and fitting curves effectively indicates the degree of fatigue damage caused to the CSB.
{"title":"Fatigue monitoring of coated steel belts by means of magnetic inspection","authors":"Sunqiang Liu, Guisuo Xia, Zhihui Wen, Qiwei Cai, Mingliang Liao","doi":"10.1784/insi.2023.65.3.153","DOIUrl":"https://doi.org/10.1784/insi.2023.65.3.153","url":null,"abstract":"Coated steel belts (CSBs) are the primary load-bearing components of elevators. As a result, they may experience severe fatigue failure during their long-term service. In this study, a flexible fatigue fixture for CSBs is designed to simulate the CSB fatigue damage process for implementing\u0000 a tensile fatigue test. The magnetic induction intensity signal on the surface of the CSB in a geomagnetic field environment is recorded using a high-precision weak magnetic sensor. Moreover, the CSB fatigue damage process is monitored online via the acquired magnetic induction intensity value.\u0000 The fatigue test results indicate the following: the variation in the magnetic induction intensity signal curve can reflect the entire fatigue failure process when the CSB is under stress; the fatigue failure process of the steel wire inside the CSB does not occur smoothly as its progress\u0000 occurs in stages; and the variation trend in the residual value between the magnetic induction intensity and fitting curves effectively indicates the degree of fatigue damage caused to the CSB.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116852814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1784/insi.2023.65.3.133
Ting Li, Jingao Su, Nina Li, Han Xu, Yue Chang
The ultrasonic testing method is commonly used to detect the internal defects of wind turbine blades, but difficulty is found in judging the echo position due to the waveform superposition caused by the thin web. In this paper, an improved matching tracking algorithm is proposed to decompose the ultrasonic detection echo of wind turbine blades. This method extracts the time-delay parameter of the echo to estimate the time-of-flight (TOF), which provides the necessary information for further judgement of hidden defects in the wind turbine blades. The effectiveness of the proposed method is verified via simulation experiments and real tests.
{"title":"Investigation of wind turbine blade ultrasonic pulse-echo signal decomposition based on the matching pursuit algorithm","authors":"Ting Li, Jingao Su, Nina Li, Han Xu, Yue Chang","doi":"10.1784/insi.2023.65.3.133","DOIUrl":"https://doi.org/10.1784/insi.2023.65.3.133","url":null,"abstract":"The ultrasonic testing method is commonly used to detect the internal defects of wind turbine blades, but difficulty is found in judging the echo position due to the waveform superposition caused by the thin web. In this paper, an improved matching tracking algorithm is proposed to\u0000 decompose the ultrasonic detection echo of wind turbine blades. This method extracts the time-delay parameter of the echo to estimate the time-of-flight (TOF), which provides the necessary information for further judgement of hidden defects in the wind turbine blades. The effectiveness of\u0000 the proposed method is verified via simulation experiments and real tests.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125162280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1784/insi.2023.65.3.146
Xiaohui Yang, Z. Jia, Long Chen, Haifeng Pu, Song Yang
The metal magnetic memory (MMM) technique is a promising non-destructive inspection method that is sensitive to early damage due to stress concentration in ferromagnetic components. However, quantitative analysis methods for evaluating the stress concentration induced by local plastic deformation have not yet been sufficiently studied due to the lack of a reasonable numerical simulation method. Based on the Jiles-Atherton (J-A) magneto-plastic model, which considers the combined effects of residual stress and strain, the change in the behaviour of residual magnetic field (RMF) signals in an X80 pipeline steel specimen with an indentation is calculated in this paper using finite element (FE) simulations, while systematic experimental research is also carried out. The results show that the model-predicted RMF signals are consistent with the experimental data, which demonstrates the validity of the numerical simulation method. Moreover, the comparison indicates that the RMF FE simulations can provide an effective and reliable way to determine the location and the degree of deformation-induced stress concentration. In addition, the effect of the residual stress and strain on the surface magnetic field and the model is discussed. The results of this study help to improve the accuracy of the MMM technique for evaluating the stress concentration caused by local plastic deformation.
{"title":"A numerical simulation method of residual magnetic field signals for evaluating deformation-induced stress concentration in ferromagnetic materials","authors":"Xiaohui Yang, Z. Jia, Long Chen, Haifeng Pu, Song Yang","doi":"10.1784/insi.2023.65.3.146","DOIUrl":"https://doi.org/10.1784/insi.2023.65.3.146","url":null,"abstract":"The metal magnetic memory (MMM) technique is a promising non-destructive inspection method that is sensitive to early damage due to stress concentration in ferromagnetic components. However, quantitative analysis methods for evaluating the stress concentration induced by local plastic\u0000 deformation have not yet been sufficiently studied due to the lack of a reasonable numerical simulation method. Based on the Jiles-Atherton (J-A) magneto-plastic model, which considers the combined effects of residual stress and strain, the change in the behaviour of residual magnetic field\u0000 (RMF) signals in an X80 pipeline steel specimen with an indentation is calculated in this paper using finite element (FE) simulations, while systematic experimental research is also carried out. The results show that the model-predicted RMF signals are consistent with the experimental data,\u0000 which demonstrates the validity of the numerical simulation method. Moreover, the comparison indicates that the RMF FE simulations can provide an effective and reliable way to determine the location and the degree of deformation-induced stress concentration. In addition, the effect of the\u0000 residual stress and strain on the surface magnetic field and the model is discussed. The results of this study help to improve the accuracy of the MMM technique for evaluating the stress concentration caused by local plastic deformation.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114585017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1784/insi.2023.65.2.95
Stephen W. Hurrell, P. Charlton, S. Mosey, O. Rees-Lloyd, R. Lewis
Electromagnetic acoustic transducers (EMATs) are well-established as a means of ultrasonic wave generation and reception without the use of a mechanical coupling. When comprising a bias magnetic field and a meander-line coil (MLC), these waves propagate at an angle normal to the emission surface. With the appropriate frequency, the propagation pathway of these ultrasonic waves can be steered to a particular angle. This paper presents the methodology used to find the steering limit of an MLC EMAT and the results from simulations and experimental validations on aluminium. The results show that the maximum shear wave amplitude occurred at around 30°, the steering limit was approximately 50° and the simulations were validated by the experimental set-up to a satisfactory degree.
{"title":"Study on the Steering Capability of A Meander-line Coil EMAT","authors":"Stephen W. Hurrell, P. Charlton, S. Mosey, O. Rees-Lloyd, R. Lewis","doi":"10.1784/insi.2023.65.2.95","DOIUrl":"https://doi.org/10.1784/insi.2023.65.2.95","url":null,"abstract":"Electromagnetic acoustic transducers (EMATs) are well-established as a means of ultrasonic wave generation and reception without the use of a mechanical coupling. When comprising a bias magnetic field and a meander-line coil (MLC), these waves propagate at an angle normal to the emission\u0000 surface. With the appropriate frequency, the propagation pathway of these ultrasonic waves can be steered to a particular angle. This paper presents the methodology used to find the steering limit of an MLC EMAT and the results from simulations and experimental validations on aluminium. The\u0000 results show that the maximum shear wave amplitude occurred at around 30°, the steering limit was approximately 50° and the simulations were validated by the experimental set-up to a satisfactory degree.","PeriodicalId":344397,"journal":{"name":"Insight - Non-Destructive Testing and Condition Monitoring","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128708718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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